Whisper Large V3 Persian Common Voice 17

🚀 Whisper Large v3 - Persian (Common Voice 17)

Whisper Large v3 fine-tuned on Common Voice 17 for enhanced Persian automatic speech recognition, offering lower error rates and greater accuracy.

🚀 Quick Start

Whisper Large v3 has been fine-tuned on Common Voice 17, leveraging over 250,000 Persian audio samples. This is a significant improvement over earlier models trained on Common Voice 11, which only had 83,000 samples. The larger dataset has led to a lower Word Error Rate (WER), enhancing the model's accuracy and robustness in recognizing Persian speech.

This update is a major step forward in Persian ASR, and we hope it benefits the Persian-speaking community, making high-quality speech recognition more accessible and reliable. 🚀

📦 Installation

The installation steps are mainly about using the transformers library. You can install it via the following command if not already installed:

pip install transformers

💻 Usage Examples

Basic Usage

from transformers import pipeline

asr_pipe = pipeline(
    "automatic-speech-recognition",
    model="msghol/whisper-large-v3-persian-common-voice-17",
    chunk_length_s=30
)

text = asr_pipe("your_file")["text"]
print(text)

📚 Documentation

Model Information

Notes

⚠️ Important Note

Since the fine tuning process does not include any timestamps, the model can not return any timestamps. Even when you are trying to return it, you would encounter an Error. The solution is to chunk audio files into smaller chunks.

💡 Usage Tip

Further fine tuning would definitely increase the accuracy of the model. We are currently looking for sponserships for Hardware and ASR dataset collaborations.

Citation

@misc{whisper_persian_cv17,
  author = {Mohammad Sadegh Gholizadeh},
  title = {Whisper Large v3 - Persian (Common Voice 17)},
  year = {2025},
  url = {https://huggingface.co/msghol/whisper-large-v3-persian-common-voice-17}
}

📄 License

This project is licensed under the Apache-2.0 license.